by Sateesh Seetharamiah, CEO, Edge Platforms, EdgeVerve
While technology evolves continuously, there are transformative moments in time where a convergence of several factors creates a tectonic shift in the market. We’ve seen that happen with the Internet and the digital-first revolution that gave rise to Facebook (now Meta), Grab, Snapchat, etc. We are living through another transformative right now, one that is powered by Generative AI. Since ChatGPT exploded on the scene, investments in AI have seen a rise. Gartner found that 70% of companies are currently in exploration mode with Generative AI.
We are now firmly in the AI-first era. Where in the next two years, AI and automation will play a critical role in business success. This is when we’ll see the next Uber and Netflix emerge, creating new business models with AI at their core. While the mobile revolution favored startups, large enterprises may have the most to gain in the AI era. We are already seeing companies like Adobe (with Firefly), Tesla, Salesforce (Einstein), and Google make giant leaps by embedding AI into their workflows. And they are seeing massive gains in operational efficiencies, customer experience, and revenues.
Companies are now investing 13x more in AI than a decade ago. Yet, 70% of companies do not scale digital solutions beyond the pilot, and 65% fail to achieve the intended results. What’s separating the few companies that succeed with AI from those who fail? The answer lies in their approach and mindset towards AI.
AI-first businesses need a new operating model
The AI trailblazers don’t just use AI; they are built around it and have integrated it into end-to-end user journeys. These companies are not just adopting AI; they are redefining what’s possible by placing AI at the heart of their operations. This is not just tech adoption but a shift in mindset.
The typical piecemeal approach of tech adoption is not going to work for artificial intelligence. Realizing the pinnacle of AI-led efficiency – autonomous operations and straight-through processing (STP) – requires a free flow of data and information across the business. Only when AI insights are seamlessly integrated into workflows can companies leverage them to enhance decision-making, optimize operations, and create unparalleled customer experiences.
Unfortunately, most businesses are ill-prepared for this eventuality. They are plagued with siloes and sub-optimal tech investments and operate with a complex web of modern and legacy point solutions. This traditional operating model limits business growth and responsiveness.
An AI-first business needs a new operating model that involves rethinking workflows, smashing organizational siloes, and fostering seamless human-AI collaboration. They need a pivot from a “Siloed” to a “Platform-based” operating model that is horizontally connected, leverages an integrated data foundation, drives rapid deployment of AI-powered applications, and enables exponential growth in scale, scope, and learning.
A platform-based operating model ensures organizations have consistent, end-to-end processes and complete visibility into people, processes, and partners. It aids in bridging the data gaps and creating meaningful intelligence from the entire data across organizations. Most importantly, a platform can sit on top of the existing infrastructure to unlock the full potential of existing and future tech investments.
How businesses are reaping the benefits of an AI-first approach
Businesses adopting an AI-first model realize the importance of a platform-based approach. They know that they can reap substantial gains only when they build new workflows (with an AI core) for their operations, interactions, and innovations. Take the case of Ant Financial, an AI-centric business that serves a staggering 700 million customers with a few thousand employees while acing customer experience. It disburses loans in a matter of minutes with zero manual intervention. Traditional banking setups take days, if not weeks, to deliver the same outcomes, with over 1.5x as many employees.
Similarly, Adobe is integrating generative AI into design workflows with Firefly, which has become the company’s most successful beta launch. In another instance, a large US financial services provider achieved 90% straight-through processing for its automated E-Sign post approval of policy application. This automation helped in the customer’s business continuity during the pandemic. Philips, on the other hand, embarked on one of the largest and most complex automation programs in the industry and improved collections by 21%.
An AI-first platform-based approach is a mandate for enterprises looking to:
- Achieve efficiencies at scale with a higher degree of straight-through processing
- Augment human potential using generative AI capabilities, and
- Attain business resilience by harnessing the power of connected networks.
The roadmap to becoming an AI-first connected enterprise
Embarking on the journey to becoming an AI-first business demands a structured and nuanced approach. It begins with a candid self-evaluation, asking pivotal questions about investment ROI, resilience, and adaptability. And then progressing across four pillars of transformation:
1. Digitize – Continuously collect, digitize, and harmonize data from within the enterprise and its extended ecosystem of partners. Capture process insights to identify areas of optimization and automation.
2. Automate – Automate processes and eliminate bottlenecks for faster, more efficient, and unbroken user journeys. Intelligently orchestrate data flows with seamless integration of applications, services, and partners across diverse environments and interfaces. Automate data acquisition and exchange across different systems/partners at scale to enhance interoperability.
3. Augment – Enhance workforce productivity and experience with AI-enhanced, unified user interfaces and alerts for proactive exception management. Integrate Generative AI into the workflow to offer contextual, on-demand information for streamlined decision-making.
4. Connect – Build data integration pipelines across data sources at speed, reducing the time to business value realization. Foster seamless, contextual interactions through text or voice across various channels, bridging departmental silos and enhancing experiences for employees, customers, and partners. Support multi-dimensional collaboration to enhance interoperability within the ecosystem.
Reimagining the future enterprise
In a world where standing still is as good as moving backward, businesses need a quantum leap from traditional approaches. The challenge and the opportunity for businesses is not just to welcome AI into their fold but to allow it to weave seamlessly into the very fabric of their business framework, unifying disparate technologies.
Businesses need to invest in creating the enterprise of the future that looks beyond one-off use cases to focus on perfecting customer centricity; that insulates business operations from underlying technology dynamics; and that employs an operating model that scales smoothly to meet the evolving AI and technology demands.